Supervised Machine Learning Techniques for Trojan Detection with Ring Oscillator Network

With the globalization of the semiconductor manufacturing process, electronic devices are powerless against malicious modification of hardware in the supply chain. The ever-increasing threat of hardware Trojan attacks against integrated circuits has spurred a need for accurate and efficient detection methods. Ring oscillator network (RON) is used to detect the Trojan by capturing the difference in power consumption; the power consumption of a Trojan-free circuit is different from the Trojan-inserted circuit. However, the process variation and measurement noise are the major obstacles to detect hardware Trojan with high accuracy. In this paper, we quantitatively compare four supervised machine learning algorithms and classifier optimization strategies for maximizing accuracy and minimizing the false positive rate (FPR). These supervised learning techniques show an improved false positive rate compared to principal component analysis (PCA) and convex hull classification by nearly 40% while maintaining > 90\% binary classification accuracy

A Non-invasive Technique to Detect Authentic/Counterfeit SRAM Chips

Many commercially available memory chips are fabricated worldwide in untrusted facilities. Therefore, a counterfeit memory chip can easily enter into the supply chain in different formats. Deploying these counterfeit memory chips into an electronic system can severely affect security and reliability domains because of their sub-standard quality, poor performance, and shorter lifespan. Therefore, a proper solution is required to identify counterfeit memory chips before deploying them in mission-, safety-, and security-critical systems. However, a single solution to prevent counterfeiting is challenging due to the diversity of counterfeit types, sources, and refinement techniques. Besides, the chips can pass initial testing and still fail while being used in the system. Furthermore, existing solutions focus on detecting a single counterfeit type (e.g., detecting recycled memory chips). This work proposes a framework that detects major counterfeit static random-access memory (SRAM) types by attesting/identifying the origin of the manufacturer. The proposed technique generates a single signature for a manufacturer and does not require any exhaustive registration/authentication process. We validate our proposed technique using 345 SRAM chips produced by major manufacturers. The silicon results show that the test scores ($F_{1}$ score) of our proposed technique of identifying memory manufacturer and part-number are 93% and 71%, respectively.Comment: This manuscript has been submitted for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

Respiratory Rate Monitoring in Clinical Environments with a Contactless Ultra-Wideband Impulse Radar-based Sensor System

Respiratory rate is an extremely important but poorly monitored vital sign for medical conditions. Current modalities for respiratory monitoring are suboptimal. This paper presents a proof of concept of a new algorithm using a contactless ultra-wideband (UWB) impulse radar-based sensor to detect respiratory rate in both a laboratory setting and in a two-subject case study in the Emergency Department. This novel approach has shown correlation with manual respiratory rate in the laboratory setting and shows promise in Emergency Department subjects. In order to improve respiratory rate monitoring, the UWB technology is also able to localize subject movement throughout the room. This technology has potential for utilization both in and out of the hospital environments to improve monitoring and to prevent morbidity and mortality from a variety of medical conditions associated with changes in respiratory rate

Towards the Avoidance of Counterfeit Memory: Identifying the DRAM Origin

Due to the globalization in the semiconductor supply chain, counterfeit dynamic random-access memory (DRAM) chips/modules have been spreading worldwide at an alarming rate. Deploying counterfeit DRAM modules into an electronic system can have severe consequences on security and reliability domains because of their sub-standard quality, poor performance, and shorter life span. Besides, studies suggest that a counterfeit DRAM can be more vulnerable to sophisticated attacks. However, detecting counterfeit DRAMs is very challenging because of their nature and ability to pass the initial testing. In this paper, we propose a technique to identify the DRAM origin (i.e., the origin of the manufacturer and the specification of individual DRAM) to detect and prevent counterfeit DRAM modules. A silicon evaluation shows that the proposed method reliably identifies off-the-shelf DRAM modules from three major manufacturers

Eulerian Phase-based Motion Magnification for High-Fidelity Vital Sign Estimation with Radar in Clinical Settings

Efficient and accurate detection of subtle motion generated from small objects in noisy environments, as needed for vital sign monitoring, is challenging, but can be substantially improved with magnification. We developed a complex Gabor filter-based decomposition method to amplify phases at different spatial wavelength levels to magnify motion and extract 1D motion signals for fundamental frequency estimation. The phase-based complex Gabor filter outputs are processed and then used to train machine learning models that predict respiration and heart rate with greater accuracy. We show that our proposed technique performs better than the conventional temporal FFT-based method in clinical settings, such as sleep laboratories and emergency departments, as well for a variety of human postures.Comment: Accepted in IEEE Sensors 202

Anti-MRSA Activity of Oxysporone and Xylitol from the Endophytic Fungus Pestalotia sp. Growing on the Sundarbans Mangrove Plant Heritiera fomes

Heritiera fomes Buch.-Ham., a mangrove plant from the Sundarbans, has adapted to a unique habitat, muddy saline water, anaerobic soil, brackish tidal activities and high microbial competition. Endophytic fungal association protects this plant from adverse environmental conditions. This plant is used in Bangladeshi folk medicine, but it has not been extensively studied phytochemically, and there is hardly any report on investigation on endophytic fungi growing on this plant. In this study, endophytic fungi were isolated from the surface sterilized cladodes and leaves of H. fomes. The antimicrobial activities were evaluated against two Gram-positive and two Gram-negative bacteria and the fungal strain, Candida albicans. Extracts of Pestalotia sp. showed activities against all test bacterial strains, except that the EtOAc extract was inactive against E. coli. The structures of the purified compounds, oxysporone and xylitol, were elucidated by spectroscopic means. The anti-MRSA potential of the isolated compounds were determined against various MRSA strains, i.e., ATCC 25923, SA-1199B, RN4220, XU212, EMRSA-15 and EMRSA-16, with MIC values ranging from 32-128 g/mL. This paper, for the first time, reports on the anti-MRSA property of oxysporone and xylitol, isolation of the endophyte Pestalotia sp. from H. fomes, and isolation of xylitol from a Pestalotia sp

EFFECTS OF ANIONS AND CATIONS OF IONIC LIQUIDS ON CLAY SWELLING: EXPERIMENTAL AND SIMULATION APPROACHES

Ionic liquids (ILs) can play a vital role in preventing clay swelling during hydraulic fracturing. Research have indicated that the length of the side chain attached to the cationic core has an effect on the inhibitor’s performance. However, the cations and polyatomic anions may also have the ability to inhibit clay swelling. In this study, five ILs were utilized to assess the effects of cations and polyatomic anions on clay swelling inhibition. The ILs’ performances were compared with a commonly used inhibitor, potassium chloride. X-ray diffraction test was used to check the mineral composition of a bentonite clay sample utilized in this research. The ability of these ILs to suppress clay swelling and their rheological properties were determined using linear swelling and rheological tests. The swelling inhibition mechanisms were studied using zeta potential, Fourier-transform infrared spectroscopy, and contact angle measurements. Moreover, COSMO-RS computer simulation was conducted to further explain the inhibition mechanisms